Aspects of the disclosure relate to electronic context determination. In particular, devices, systems, and methods for determining the context of an electronic device using sensor or application data available for analysis by a context engine.
In today's high-paced society, people can participate in a myriad of activities, visit dozens of places, and interact with tens to hundreds of people—all within a single day. Accurately estimating a person's situation or context may allow services or functionalities to be selectively presented or implemented.
Many mobile devices now include applications and sensors to collect information about an environment in which the device is operating and react to or change operational characteristics based upon that information. Such context awareness capabilities are becoming more and more prevalent in the communications industry. However, the large number of potential contexts makes it difficult to reliably and accurately estimate contexts.
Current context system infer context from senor data either instantaneously or by averaging instantaneous contexts over time. Instantaneously inferring context is challenging due to noisy mappings between user context and data.
For example, although when a user is in a meeting the most common output of a speech detector might be speech (as opposed to ‘no speech’), the most common device motion state might be device at rest, and there may typically be many Bluetooth™ devices within range, it is still possible that at the time these low-level features/inferences are computed, speech may be determined to be not present, the motion state may reveal the device to not be at rest, and there may be no Bluetooth™ devices within range. For an instantaneous context then, any single determination may be in error due to expected noise or abnormalities in context information. Merely filtering to average out these noise or abnormal readings, however, comes at the cost of dynamic response. When a boundary between two different contexts is crossed, the inference is blurred out and performance degrades.
There is a growing need for new and useful techniques and structures for implementing context awareness in communication devices.